Quan Wang

TMBserval: a statistical explainable learning model reveals weighted tumor mutation burden better categorizing therapeutic benefits

Artificial intelligence framework identifies candidate targets for drug repurposing in Alzheimer’s disease

TVAR: assessing tissue-specific functional effects of non-coding variants with deep learning

Integration of multidimensional splicing data and GWAS summary statistics for risk gene discovery

A Bayesian framework to integrate multi-level genome-scale data for Autism risk gene prioritization

Leveraging Gene-Level Prediction as Informative Covariate in Hypothesis Weighting Improves Power for Rare Variant Association Studies

DRAMS: A tool to detect and re-align mixed-up samples for integrative studies of multi-omics data